Abstract

Abstract. Black carbon (BC) is the most important light-absorbing aerosol in the atmosphere. However, sources of atmospheric BC aerosols are largely uncertain, making it difficult to assess its influence on radiative forcing and climate change. In this study, year-round light-absorption observations were conducted during 2014 using an aethalometer in Xiamen, a coastal city in Southeast China. Source apportionment of BC was performed and temporal variations in BC sources were characterized based on both light absorption measurements and a source-oriented air quality model. The annual average concentrations of BC from fossil fuel (BCff) and biomass burning (BCbb) by the aethalometer method were 2932 ± 1444 ng m−3 and 1340 ± 542 ng m−3, contributing 66.7 % and 33.3 % to total BC, respectively. A sensitivity analysis was performed with different absorption Ångström exponent (AAE) values of fossil fuel combustion (αff) and biomass burning (αbb), suggesting that the aethalometer method was more sensitive to changes in αbb than αff. BCbb contribution exhibited a clear diurnal cycle, with the highest level (37.9 %) in the evening rush hour and a seasonal pattern with the maximum (39.9 %) in winter. Conditional probability function (CPF) analysis revealed the large biomass-burning contributions were accompanied by east-northeasterly and northerly winds. Backward trajectory indicated that air masses from North and East–Central China were associated with larger biomass-burning contributions. Potential source contribution function (PSCF) and concentration-weighted trajectory (CWT) suggested that North and East–Central China and Southeast Asia were potential sources of both BCff and BCbb. The source-oriented modeling results showed that transportation, residential and open biomass burning accounting for 45.3 %, 30.1 % and 17.6 % were the major BC sources. Among the three fuel catalogs, liquid fossil fuel (46.5 %) was the largest source, followed by biomass burning (32.6 %) and coal combustion (20.9 %). Source contributions of fossil fuel combustion and biomass burning identified by the source-oriented model were 67.4 % and 32.6 %, respectively, close to those obtained by the aethalometer method. The findings provide solid support for controlling fossil fuel sources to limit the impacts of BC on climate change and environmental degradation in the relatively clean region in China.

Highlights

  • Black carbon (BC) aerosol is a vital air pollutant throughout the surface earth system and has attracted great concern regarding its multiple impacts on human health, climate change and atmospheric visibility (Bond et al, 2013; Zhuang et al, 2018, 2019; Chen et al, 2020)

  • The annual average concentrations of BC from fossil fuel (BCff) and BCbb identified by the aethalometer method with αff = 1.0 and αbb = 2.0 were 2932 ± 1444 ng m−3 and 1340 ± 542 ng m−3, accounting for 66.7 % and 33.3 % of total BC, respectively

  • A sensitivity analysis conducted by changing the αff and αbb values suggested that increase in αff or αbb values would lead to increase in BCff against BCbb, and the aethalometer method was more sensitive to changes in αbb rather than αff

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Summary

Introduction

Black carbon (BC) aerosol is a vital air pollutant throughout the surface earth system and has attracted great concern regarding its multiple impacts on human health, climate change and atmospheric visibility (Bond et al, 2013; Zhuang et al, 2018, 2019; Chen et al, 2020). Mousavi et al (2019) apportioned BC in the Milan metropolitan area to the fossil fuel and biomass-burning emission using the aethalometer model with the absorption Ångström exponent (AAE) values derived from the 14C radiocarbon analysis, highlighting the significant impact of residential wood burning on BC. Such observation-based source apportionment methods are powerful to understand the BC sources at given receptor locations. The findings help better understand the main sources and relative contributions of BC and provide valuable information to adopt effective emission reduction measures to control BC pollution in not heavily polluted regions

Observation site and measurements
Observation-based source apportionment
Potential sources of BCff and BCbb
Source-oriented modeling
Light absorption-based source apportionment of BC
Sources and transport pathways of BCff and BCbb
Source-oriented modeling-based source apportionment of BC
Conclusions
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